AC Motor Controller
A system, method, and device for monitoring an AC induction motor are disclosed. The exemplary system provides the architecture of an intelligent motor controller. On one hand, the controller has self-commission and adaptive tuning capability and can provide smooth start and stop for motor driven systems. On the other hand, the controller can provide fault detection, power metering, and history data logging, to ensure motor operates under optimal conditions. The exemplary system may have one or more sensors for monitoring characteristics of the AC induction motor and producing one or more inputs from the characteristics.
1 - 20 . (canceled)
21 . A method for controlling an AC induction motor by an intelligent soft-starter device, comprising:
adaptively controlling acceleration and deceleration of the AC induction motor to start and stop the AC induction motor;
monitoring current and voltage of the AC induction motor when the AC induction motor is at steady state;
detecting faults in the AC induction motor based on the monitored current and voltage of the AC induction motor;
calculating power parameters of the AC induction motor based on the monitored current and voltage of the AC induction motor; and
storing a history of motor performance statistics of the AC induction motor and detecting trends for performance of the AC induction motor based on the stored history of motor performance statistics.
22 . The method of claim 1 , wherein said step of adaptively controlling acceleration and deceleration of the AC induction motor comprises:
adaptively controlling a voltage of the AC induction motor based on a load of the AC induction motor using adaptive sensorless speed and flux observers.
23 . The method of claim 1 , wherein said step of adaptively controlling acceleration and deceleration of the AC induction motor comprises:
adaptively controlling a voltage of the AC induction motor based on a load of the AC induction motor using a neural network.
24 . The method of claim 1 , wherein said step of adaptively controlling acceleration and deceleration of the AC induction motor comprises:
adaptively controlling a voltage of the AC induction motor based on a load of the AC induction motor using a fuzzy logic controller.
25 . The method of claim 1 , wherein said step of detecting faults in the AC induction motor based on the monitored current and voltage of the AC induction motor comprises:
detecting mechanical faults of the AC induction motor.
26 . The method of claim 5 , wherein said step of detecting mechanical faults of the AC induction motor comprises:
detecting mechanical faults of the AC induction motor based on a Fast Fourier Transform (FFT) of the current of the AC induction motor.
27 . The method of claim 1 , wherein said step of detecting faults in the AC induction motor based on the monitored current and voltage of the AC induction motor comprises:
detecting electrical faults of the AC induction motor.
28 . The method of claim 1 , wherein said step of detecting faults in the AC induction motor based on the monitored current and voltage of the AC induction motor comprises:
detecting thermal faults of the AC induction motor.
29 . The method of claim 8 , wherein said step of detecting thermal faults of the AC induction motor comprises:
estimating a temperature of the AC motor using sensorless resistance-based temperature estimation based on a dq0 model.
30 . The method of claim 1 , wherein said power parameters of the AC induction motor comprise at least one of frequency, power factor, and reactive power.
31 . The method of claim 1 , wherein said motor performance statistics of the AC induction motor comprise at least one of maximum power consumption, minimum power consumption, average power consumption, total number of starts, and interval between starts.
32 . The method of claim 1 , further comprising:
scheduling maintenance on at least one of the AC induction motor and a load of the AC induction motor based on the stored history of motor performance statistics of the AC induction motor.